CN110956327A - Multi-robot automatic parking method, medium, terminal and device - Google Patents
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Abstract
The invention discloses a method, a medium, a terminal and a device for automatically stopping multiple robots, which comprise the following steps: when the robot reaches a target area, detecting current barrier information of the target area, inquiring a preset parking strategy table of the target area, acquiring a plurality of parking positions with distances to the nearest barrier larger than a preset value, and taking the parking position with the highest score as an optimal parking position; and controlling the robot to move to the optimal parking position, and optimizing the optimal parking position in the moving process. The invention provides a method for selecting corresponding parking positions of multiple robots through self-organization based on a consensus mechanism, which can enable the multiple robots to complete a designed station strategy in the same space and list specified formation in parallel on the premise of not depending on mutual communication among the robots and a centralized scheduling system, and meanwhile, the cost of the system is not increased, delay caused by communication environment change is avoided, and the method is suitable for wide application in the field of the multiple robots.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the field of robots, in particular to a method, medium, terminal and device for automatically stopping multiple robots.
[ background of the invention ]
With the rapid development of artificial intelligence, artificial intelligent robot dollies (hereinafter referred to as robots) are gradually present in various buildings and undertake tasks such as navigation, exhibition, delivery and the like. Under the scenes of delivery and the like requiring a large amount of delivery capacity, the working capacity of a single robot cannot meet the requirement. When multiple robots execute tasks in the same space, the robots need to form a certain standing rule under a certain specific scene and task state, so that the effects of optimizing efficiency, conforming to human social rules, being attractive and the like are achieved. For example, when elevators such as an elevator entrance and the like are used, the robot queues up in the oblique angle direction of the elevator entrance, so that people in the elevator descend before ascend, and the robot determines the sequence of entering and exiting the elevator according to the sequence of queuing. For another example, when a group of robots complete a delivery task, and stop at a certain area of a building, it is desirable that the robots automatically align themselves within an area. Generally, the robot stations are formed by relying on a unified centralized scheduling system, and the centralized scheduling system increases the cost of the whole system and depends on communication, and the problem of delay of an actual state and a transmission state is also faced.
[ summary of the invention ]
The invention provides a method, a medium, a terminal and a device for automatically stopping multiple robots, which solve the technical problems.
The technical scheme for solving the technical problems is as follows: a multi-robot automatic parking method comprises the following steps:
and 3, controlling the robot to move to the optimal parking position, and optimizing the optimal parking position in the moving process until the station effect corresponding to the preset parking strategy table is realized.
In a preferred embodiment, the method for controlling the robot to move to the optimal parking position and optimizing the optimal parking position in the moving process specifically comprises the following steps:
s301, controlling the robot to move to the optimal parking position, detecting current obstacle information again in the moving process, obtaining a new optimal parking position according to the detected current obstacle information again, updating the current optimal parking position if the score of the new optimal parking position is higher than that of the current optimal parking position, and controlling the robot to move to the new optimal parking position;
s302, in the moving process of the robot, if the current optimal parking position is detected to be inaccessible or occupied by the robot in advance, repeating the step 2, and reacquiring the optimal parking position.
In a preferred embodiment, the robot is controlled to move to the optimal parking position, and the optimal parking position is optimized during the moving process, the method further includes step S303, when the robot reaches the current optimal parking position, step 2 is repeated, and if a new optimal parking position score is higher than the current optimal parking position score, the robot is controlled to move to the new optimal parking position again.
In a preferred embodiment, the method further comprises a coordinate system alignment step, specifically: before the multiple robots move to the target area, the coordinate systems among the multiple robots are aligned by using the same pre-scanned space map by the multiple robots, using the same positioning system by the multiple robots and/or establishing a unified coordinate system by the multiple robots aiming at the same identification characteristics.
In a preferred embodiment, the method further includes a docking policy table establishing step, specifically:
s001, establishing a grid array for representing a spatial position;
s002, associating a score value with each grid of the grid array according to a preset station effect, and establishing a preset parking policy table, wherein the score of the grid is in direct proportion to the tendency of the robot to park on the grid; or scoring each grid association of the grid array and a preset parking attribute according to a preset station effect, and storing and indexing the preset parking attribute by adopting a two-dimensional array or a one-dimensional array while establishing a preset parking policy table.
A second aspect of the embodiments of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for automatically docking multiple robots is implemented.
A third aspect of the embodiments of the present invention provides a multi-robot automatic docking terminal, including the computer-readable storage medium and a processor, where the processor implements the steps of the multi-robot automatic docking method when executing a computer program on the computer-readable storage medium.
A fourth aspect of the embodiments of the present invention provides an automatic parking apparatus for multiple robots, comprising a determining module, an optimal position obtaining module, and an optimizing module,
the judging module is used for judging whether the robot reaches a target area in the moving process, and if so, the optimal position obtaining module is executed;
the optimal position acquisition module is used for detecting the current barrier information of a target area, inquiring a preset parking strategy table of the target area, acquiring a plurality of parking positions with the distance from the nearest barrier larger than a preset value, and taking the parking position with the highest score in the plurality of parking positions as the optimal parking position;
the optimization module is used for controlling the robot to move to the optimal parking position and optimizing the optimal parking position in the moving process until the station effect corresponding to the preset parking strategy table is achieved.
In a preferred embodiment, the optimization module specifically includes:
the first updating unit is used for controlling the robot to move to the optimal parking position, detecting the current obstacle information again in the moving process, acquiring a new optimal parking position according to the detected current obstacle information again, updating the current optimal parking position if the score of the new optimal parking position is higher than that of the current optimal parking position, and controlling the robot to move to the new optimal parking position;
and the second updating unit is used for driving the optimal position obtaining module to obtain the optimal parking position again if the current optimal parking position is detected to be unreachable or occupied by the robot in a preemptive mode in the moving process of the robot.
In a preferred embodiment, the optimization module further includes a third updating unit, and the third updating unit is specifically configured to, after the robot reaches the current optimal parking position, drive the optimal position obtaining module to detect again, and if there is a new optimal parking position score higher than the current optimal parking position, control the robot to move to the new optimal parking position again.
In a preferred embodiment, the multi-robot automatic docking device further includes a coordinate system pre-alignment module, and the coordinate system pre-alignment module is specifically configured to align coordinate systems among the plurality of robots by using the same pre-scanned space map by the plurality of robots, using the same positioning system by the plurality of robots, and/or establishing a unified coordinate system for the same identification feature by the plurality of robots before the plurality of robots move to the target area.
In a preferred embodiment, the multi-robot automatic docking apparatus further includes a docking policy table establishing module, where the docking policy table establishing module specifically includes:
a first establishing unit for establishing a grid array for characterizing spatial positions;
the second establishing unit is used for associating a score value with each grid of the grid array according to a preset station effect and establishing a preset parking strategy table, wherein the score of the grid is in direct proportion to the tendency of the robot to park on the grid; or scoring each grid association of the grid array and a preset parking attribute according to a preset station effect, and storing and indexing the preset parking attribute by adopting a two-dimensional array or a one-dimensional array while establishing a preset parking policy table.
The invention provides a method for selecting corresponding parking positions of multiple robots through self-organization based on a consensus mechanism, which can enable the multiple robots to complete a designed station strategy in the same space and list specified formation in parallel on the premise of not depending on mutual communication among the robots and a centralized scheduling system, and meanwhile, the cost of the system is not increased, delay caused by communication environment change is avoided, and the method is suitable for wide application in the field of the multiple robots.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic flow chart of a multi-robot automatic docking method provided in embodiment 1;
FIG. 2 is a schematic view of the multi-robot automatic docking apparatus provided in embodiment 2;
FIG. 3 is a schematic structural diagram of a multi-robot automatic docking terminal provided in embodiment 3;
FIGS. 4a and 4b are graphical display effects of two predetermined parking policy tables according to embodiment 1;
fig. 5a and 5b are schematic diagrams of stations where the robot stops according to two preset stop strategies table in embodiment 1.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantageous effects of the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and the detailed description. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a schematic flow chart of a multi-robot automatic docking method provided in embodiment 1 of the present invention, as shown in fig. 1, including the following steps:
and 3, controlling the robot to move to the optimal parking position, and optimizing the optimal parking position in the moving process until the station effect corresponding to the preset parking strategy table is realized.
The embodiment provides a method for selecting corresponding parking positions of multiple robots through self-organization based on a consensus mechanism, and the method can enable the multiple robots to complete a designed station strategy in the same space and list designated queue forms on the premise of not depending on mutual communication among the robots and a centralized scheduling system, simultaneously can not increase the system cost, can not cause delay due to communication environment change, and is suitable for wide application in the field of the multiple robots.
The above examples are described in detail below.
The robot in this embodiment includes, but is not limited to, unmanned equipment, smart mobile equipment, remote sensing mobile equipment, etc., and the robot possesses various sensors, such as lidar, infrared, supersound, structured light, vision, binocular system, etc., can perceive and model surrounding obstacles, has the ability of autonomous movement and spatial localization. In order to ensure the automatic parking effect of the robot, the coordinate systems of the plurality of robots can be mutually aligned, so that the robots can be ensured to have consistent understanding on the physical positions. The coordinate system alignment method specifically comprises the following steps: before the multiple robots move to the target area, the same pre-scanned space map is used by the multiple robots; the multiple robots use the same set of positioning system, such as positioning systems based on GPS, Wifi signals, UWB and the like based on multipoint signal difference positioning; and/or multiple robots establishing a unified coordinate system for the same identifying features, such as markers with specific optical reflection parameters, objects with specific visual attributes or features, and the like, thereby aligning the coordinate system between multiple robots.
In order to achieve the preset robot parking effect, a parking policy table is also required to be established in advance, so that multiple robots follow the same set of parking policies, and the parking policy table mainly describes the tendency of the robots to park at different positions within a certain space range. The establishing of the docking policy table specifically comprises the following steps:
and S001, establishing a grid array for representing the spatial position, and for the specified spatial range, using the grid array with the size of N x M to represent the spatial position. The larger the spatial scale of the single grid representation, the lower the position accuracy and the smaller the required storage space.
And S002, associating a score value with each grid of the grid array according to a preset station effect, and establishing a preset parking strategy table, wherein the score of the grid is in direct proportion to the tendency of the robot to park at the grid, namely the score value is larger, and the score value represents that the robot tends to park at the point. Each grid of the grid array may also be scored according to a preset station effect and a preset parking attribute, such as an angle of a tilt parking at this point, and then the preset parking attribute may be stored and indexed using a two-dimensional array or a one-dimensional array of size N × M while establishing a preset parking policy table.
FIGS. 4a and 4b are graphical representations of two predetermined parking strategy tables according to a preferred embodiment, and FIG. 4a is a diagram illustrating an array parking strategy, in which the score of each lower row is smaller than that of the upper row, and the score of the left side is larger than that of the right side in the same row, so that the robot tends to park from top to bottom and from left to right in sequence; fig. 4b represents a diagonal queuing stop strategy, which can be used for queuing in an elevator scenario, with a higher score at one angular direction than at other angular directions, and with a lower score at the same angular direction, the farther away from the target point.
The preset docking policy table described above performs a fast table lookup operation when it has been pre-calculated, stored and ordered for use within each robot. When the robot receives a task, the task information includes the specified preset stop policy table information, and when the robot moves to a target point, the robot needs to find a stop position according to the preset stop policy table, which specifically includes:
1. after receiving a task, the robot navigates to move to a target point, and when the robot reaches a region near the target point, namely a preset target region, the current obstacle information of the target region is detected through a sensor;
2. then, inquiring a specified preset parking strategy table, finding out the optimal parking position with the highest score and the distance from the closest obstacle to be greater than the preset value, and recording the optimal parking position and the corresponding score
3. And then moving to the optimal parking position, continuously detecting the current barrier information in the moving process, acquiring a new optimal parking position, updating the current optimal parking position if the score of the new optimal parking position is higher than that of the current optimal parking position, controlling the robot to move to the new optimal parking position, and recording the new optimal parking position and the corresponding score.
4. In the moving process of the robot, if the current optimal parking position is detected to be unreachable or occupied by the robot in advance, the current optimal parking position is abandoned, the optimal parking position is searched again, and the robot moves to the optimal parking position.
5. After the robot reaches the current optimal stop position, the optimal stop position under the current obstacle condition is calculated again, if a new optimal stop position with a higher score value occurs, the robot continues to move to the position, and jumps to step 3, and repeats until the stop position reached by the robot is the current obstacle position with the highest score value, as shown in fig. 5a and 5b, fig. 5a is a schematic diagram of the robot station formed by multiple robots all according to the stop strategy of fig. 4a, and fig. 5b is a schematic diagram of the robot station formed by multiple robots all according to the stop strategy of fig. 4 b.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for automatically stopping the multiple robots is realized.
Fig. 2 is a schematic structural diagram of a multi-robot automatic docking device according to embodiment 2 of the present invention, as shown in fig. 2, including a determining module 100, an optimal position obtaining module 200 and an optimizing module 300,
the judging module 100 is used for judging whether the robot reaches a target area in the moving process, and if so, executing an optimal position obtaining module;
the optimal position obtaining module 200 is configured to detect current obstacle information of a target area, query a preset parking policy table of the target area, obtain a plurality of parking positions having a distance greater than a preset value from a nearest obstacle, and use a parking position with a highest score among the plurality of parking positions as an optimal parking position;
the optimization module 300 is configured to control the robot to move to the optimal parking position, and optimize the optimal parking position in the moving process until a station effect corresponding to the preset parking policy table is achieved.
In a preferred embodiment, the optimization module 300 specifically includes:
a first updating unit 301, configured to control the robot to move to the optimal stop position, detect current obstacle information again in the moving process, obtain a new optimal stop position according to the current obstacle information detected again, update the current optimal stop position if the score of the new optimal stop position is higher than that of the current optimal stop position, and control the robot to move to the new optimal stop position;
a second updating unit 302, configured to, during the movement of the robot, drive the optimal position obtaining module to obtain the optimal stop position again if it is detected that the current optimal stop position is not reachable or is occupied preemptively.
In a preferred embodiment, the optimization module 300 further includes a third updating unit 303, where the third updating unit 303 is specifically configured to drive the optimal position obtaining module to detect again after the robot reaches the current optimal stop position, and if there is a new optimal stop position score higher than the current optimal stop position, control the robot to move to the new optimal stop position again.
In a preferred embodiment, the multi-robot automatic docking apparatus further includes a coordinate system pre-alignment module 400, where the coordinate system pre-alignment module 400 is specifically configured to align coordinate systems between the plurality of robots by using the same pre-scanned space map for the plurality of robots, using the same positioning system for the plurality of robots, and/or establishing a uniform coordinate system for the same identification feature for the plurality of robots before the plurality of robots move to the target area.
In a preferred embodiment, the multi-robot automatic docking apparatus further includes a docking policy table establishing module 500, and the docking policy table establishing module 500 specifically includes:
a first establishing unit 501, configured to establish a grid array for characterizing spatial locations;
a second establishing unit 501, configured to associate a score value with each grid of the grid array according to a preset station effect, and establish a preset parking policy table, where the score of the grid is directly proportional to a tendency of the robot to park in the grid; or scoring each grid association of the grid array and a preset parking attribute according to a preset station effect, and storing and indexing the preset parking attribute by adopting a two-dimensional array or a one-dimensional array while establishing a preset parking policy table.
The embodiment of the invention also provides a multi-robot automatic parking terminal which comprises the computer readable storage medium and a processor, wherein the processor realizes the steps of the multi-robot automatic parking method when executing the computer program on the computer readable storage medium. Fig. 3 is a schematic structural diagram of a multi-robot automatic stop terminal according to embodiment 3 of the present invention, and as shown in fig. 3, the multi-robot automatic stop terminal 8 according to this embodiment includes: a processor 80, a readable storage medium 81 and a computer program 82 stored in said readable storage medium 81 and executable on said processor 80. The processor 80, when executing the computer program 82, implements the steps in the various method embodiments described above, such as steps 1 through 3 shown in fig. 1. Alternatively, the processor 80, when executing the computer program 82, implements the functions of the modules in the above-described device embodiments, such as the functions of the modules 100 to 300 shown in fig. 2.
Illustratively, the computer program 82 may be partitioned into one or more modules that are stored in the readable storage medium 81 and executed by the processor 80 to implement the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions that describe the execution of the computer program 82 in the multi-robot automated docking terminal 8.
The multi-robot automated docking terminal 8 may include, but is not limited to, a processor 80, a readable storage medium 81. Those skilled in the art will appreciate that FIG. 3 is merely an example of a multi-robot automated docking terminal 8, and does not constitute a limitation of multi-robot automated docking terminal 8, and may include more or fewer components than shown, or some components in combination, or different components, e.g., the multi-robot automated docking terminal may further include a power management module, an arithmetic processing module, an input-output device, a network access device, a bus, etc.
The Processor 80 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The readable storage medium 81 may be an internal storage unit of the multi-robot automatic docking terminal 8, such as a hard disk or a memory of the multi-robot automatic docking terminal 8. The readable storage medium 81 may also be an external storage device of the multi-robot automatic parking terminal 8, such as a plug-in hard disk provided on the multi-robot automatic parking terminal 8, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the readable storage medium 81 may also include both an internal storage unit and an external storage device of the multi-robot automatic parking terminal 8. The readable storage medium 81 is used to store the computer program and other programs and data required for the multi-robot automatic docking terminal. The readable storage medium 81 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and method steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The invention is not limited solely to that described in the specification and embodiments, and additional advantages and modifications will readily occur to those skilled in the art, so that the invention is not limited to the specific details, representative apparatus, and illustrative examples shown and described herein, without departing from the spirit and scope of the general concept as defined by the appended claims and their equivalents.
Claims (10)
1. A multi-robot automatic parking method is characterized by comprising the following steps:
step 1, judging whether the robot reaches a target area in the moving process, if so, executing step 2, and if not, continuing to move;
step 2, detecting current barrier information of a target area, inquiring a preset parking strategy table of the target area, acquiring a plurality of parking positions with distances to the nearest barrier larger than a preset value, and taking the parking position with the highest score in the plurality of parking positions as an optimal parking position;
and 3, controlling the robot to move to the optimal parking position, and optimizing the optimal parking position in the moving process until the station effect corresponding to the preset parking strategy table is realized.
2. The multi-robot automatic docking method according to claim 1, wherein the robot is controlled to move to the optimal docking position, and the optimal docking position is optimized during the movement, and the method specifically comprises the following steps:
s301, controlling the robot to move to the optimal parking position, detecting current obstacle information again in the moving process, obtaining a new optimal parking position according to the detected current obstacle information again, updating the current optimal parking position if the score of the new optimal parking position is higher than that of the current optimal parking position, and controlling the robot to move to the new optimal parking position;
s302, in the moving process of the robot, if the current optimal parking position is detected to be inaccessible or occupied by the robot in advance, repeating the step 2, and reacquiring the optimal parking position.
3. The method as claimed in claim 2, wherein the robot is controlled to move to the optimal parking position and the optimal parking position is optimized during the moving, and further comprising step S303, when the robot reaches the current optimal parking position, repeating step S2, and if there is a new optimal parking position score higher than the current optimal parking position, the robot is controlled to move to the new optimal parking position again.
4. The multi-robot automatic docking method according to any one of claims 1 to 3, further comprising a coordinate system alignment step, specifically: before the multiple robots move to the target area, the coordinate systems among the multiple robots are aligned by using the same pre-scanned space map by the multiple robots, using the same positioning system by the multiple robots and/or establishing a unified coordinate system by the multiple robots aiming at the same identification characteristics.
5. The multi-robot automatic docking method as claimed in claim 4, further comprising a docking policy table establishing step, specifically:
s001, establishing a grid array for representing a spatial position;
s002, associating a score value with each grid of the grid array according to a preset station effect, and establishing a preset parking policy table, wherein the score of the grid is in direct proportion to the tendency of the robot to park on the grid; or scoring each grid association of the grid array and a preset parking attribute according to a preset station effect, and storing and indexing the preset parking attribute by adopting a two-dimensional array or a one-dimensional array while establishing a preset parking policy table.
6. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the multi-robot automatic docking method according to any one of claims 1 to 5.
7. A multi-robot automatic docking terminal comprising the computer-readable storage medium of claim 6 and a processor, which when executing a computer program on the computer-readable storage medium implements the steps of the multi-robot automatic docking method of any one of claims 1 to 5.
8. A multi-robot automatic parking device is characterized by comprising a judging module, an optimal position obtaining module and an optimizing module,
the judging module is used for judging whether the robot reaches a target area in the moving process, and if so, the optimal position obtaining module is executed;
the optimal position acquisition module is used for detecting the current barrier information of a target area, inquiring a preset parking strategy table of the target area, acquiring a plurality of parking positions with the distance from the nearest barrier larger than a preset value, and taking the parking position with the highest score in the plurality of parking positions as the optimal parking position;
the optimization module is used for controlling the robot to move to the optimal parking position and optimizing the optimal parking position in the moving process until the station effect corresponding to the preset parking strategy table is achieved.
9. The multi-robot automatic docking device as claimed in claim 8, wherein the optimization module specifically comprises:
the first updating unit is used for controlling the robot to move to the optimal parking position, detecting the current obstacle information again in the moving process, acquiring a new optimal parking position according to the detected current obstacle information again, updating the current optimal parking position if the score of the new optimal parking position is higher than that of the current optimal parking position, and controlling the robot to move to the new optimal parking position;
and the second updating unit is used for driving the optimal position obtaining module to obtain the optimal parking position again if the current optimal parking position is detected to be unreachable or occupied by the robot in a preemptive mode in the moving process of the robot.
10. The multi-robot automatic docking method according to claim 8 or 9, further comprising a docking policy table establishing module, wherein the docking policy table establishing module specifically comprises:
a first establishing unit for establishing a grid array for characterizing spatial positions;
the second establishing unit is used for associating a score value with each grid of the grid array according to a preset station effect and establishing a preset parking strategy table, wherein the score of the grid is in direct proportion to the tendency of the robot to park on the grid; or scoring each grid association of the grid array and a preset parking attribute according to a preset station effect, and storing and indexing the preset parking attribute by adopting a two-dimensional array or a one-dimensional array while establishing a preset parking policy table.
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